Edit bounds dialog fixed, added showColoredMessage() to GUI

pymead/core/constraint_graph.py

@@ -720,220 +720,3 @@ def update_points(self, constraint: GeoCon, new_x: np.ndarray):
 
 class OverConstrainedError(Exception):
     pass
-
-
-def main():
-    import matplotlib.pyplot as plt
-
-    p1 = Point(0.0, 0.0, "p1")
-    p2 = Point(0.3, 0.3, "p2")
-    p3 = Point(0.4, 0.6, "p3")
-    p4 = Point(0.8, -0.1, "p4")
-    p5 = Point(0.2, 0.6, "p5")
-    points = [p1, p2, p3, p4, p5]
-
-    original_x = [p.x().value() for p in points]
-    original_y = [p.y().value() for p in points]
-    plt.plot(original_x, original_y, ls="none", marker="o", color="indianred")
-    plt.gca().set_aspect("equal")
-
-    cnstr1 = DistanceConstraint(p1, p2, 1.0, "d1")
-    cnstr2 = DistanceConstraint(p2, p3, 0.8, "d2")
-    cnstr3 = DistanceConstraint(p2, p4, 0.4, "d3")
-    cnstr4 = DistanceConstraint(p1, p5, 1.2, "d4")
-    cnstr5 = DistanceConstraint(p3, p1, 0.6, "d5")
-    graph = ConstraintGraph()
-
-    graph.add_constraint(cnstr1)
-    graph.add_constraint(cnstr2)
-    graph.add_constraint(cnstr3)
-    graph.add_constraint(cnstr4)
-    graph.add_constraint(cnstr5)
-
-    print(f"{np.hypot(p1.x().value() - p2.x().value(), p1.y().value() - p2.y().value())}")
-    print(f"{np.hypot(p3.x().value() - p2.x().value(), p3.y().value() - p2.y().value())}")
-    print(f"{np.hypot(p1.x().value() - p3.x().value(), p1.y().value() - p3.y().value())}")
-
-    print(f"{p2 = }")
-
-    # new_x = [p.x().value() for p in points]
-    # new_y = [p.y().value() for p in points]
-    # plt.plot(new_x, new_y, ls="none", marker="s", color="mediumaquamarine", mfc="#aaaaaa88")
-    # plt.show()
-    #
-    # graph.move_point(p2, 0.8, 0.6)
-    #
-    # print(f"{np.hypot(p1.x().value() - p2.x().value(), p1.y().value() - p2.y().value())}")
-    # print(f"{np.hypot(p3.x().value() - p2.x().value(), p3.y().value() - p2.y().value())}")
-    # print(f"{np.hypot(p1.x().value() - p3.x().value(), p1.y().value() - p3.y().value())}")
-
-    new_x = [p.x().value() for p in points]
-    new_y = [p.y().value() for p in points]
-    plt.plot(original_x, original_y, ls="none", marker="o", color="indianred")
-    plt.plot(new_x, new_y, ls="none", marker="s", color="steelblue", mfc="#aaaaaa88")
-    plt.show()
-
-    pass
-
-
-def main2():
-    import matplotlib.pyplot as plt
-    # Initialize the graph
-    g = ConstraintGraph()
-
-    # Add the points
-    p1 = Point(0.0, 0.0, "p1")
-    p2 = Point(0.4, 0.1, "p2")
-    p3 = Point(0.6, 0.0, "p3")
-    p4 = Point(0.2, 0.8, "p4")
-    p5 = Point(1.0, 1.3, "p5")
-    points = [p1, p2, p3, p4, p5]
-    for point in points:
-        g.add_point(point)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mec="indianred", mfc="indianred", fillstyle="left", markersize=10)
-
-    # Add the constraints
-    d1 = DistanceConstraint(p1, p2, 0.2, "d1")
-    d2 = DistanceConstraint(p2, p4, 1.5, "d2")
-    d3 = DistanceConstraint(p2, p3, 0.5, "d3")
-    d4 = DistanceConstraint(p3, p5, 1.4, "d4")
-    perp3 = Perp3Constraint(p1, p2, p4, "L1")
-    parl = Parallel4Constraint(p2, p4, p3, p5, "//1")
-    aparl3 = AntiParallel3Constraint(p1, p2, p3, "ap1")
-    constraints = [d1, d2, d3, d4, perp3, parl, aparl3]
-    for constraint in constraints:
-        g.add_constraint(constraint)
-        plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o",
-                 mec="indianred", mfc="indianred", fillstyle="left", markersize=10)
-        plt.show()
-
-    d4.param().set_value(4.0)
-    d4.param().set_value(5.0)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o",
-             mfc="steelblue", mec="steelblue", fillstyle="right", markersize=10)
-    for p in points:
-        plt.text(p.x().value() + 0.02, p.y().value() + 0.02, p.name())
-    plt.gca().set_aspect("equal")
-
-    plt.show()
-
-    labels = {p: p.name() for p in g.nodes}
-    subax1 = plt.subplot(121)
-    networkx.draw(g, with_labels=True, labels=labels)
-
-    # for node in networkx.dfs_preorder_nodes(g, source=p1):
-    #     if isinstance(node, GeoCon):
-    #         print(f"{node = }")
-
-    # cycle_basis = networkx.cycle_basis(g)
-    # # for c in cycle_basis:
-    # #     print(f"{c = }")
-    # simple_cycles = networkx.chordless_cycles(g)
-    # for simple_cycle in simple_cycles:
-    #     print(simple_cycle)
-
-    plt.show()
-    pass
-
-
-def main3():
-    import matplotlib.pyplot as plt
-    # Initialize the graph
-    g = ConstraintGraph()
-
-    # Add the points
-    p1 = Point(0.0, 0.0, "p1")
-    p2 = Point(0.4, 0.1, "p2")
-    p3 = Point(0.6, 0.0, "p3")
-    points = [p1, p2, p3]
-    for point in points:
-        g.add_point(point)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mec="indianred", mfc="indianred", fillstyle="left", markersize=10)
-
-    # Add the constraints
-    d1 = DistanceConstraint(p1, p2, 0.6, "d1")
-    d2 = DistanceConstraint(p2, p3, 1.0, "d2")
-    d3 = DistanceConstraint(p1, p3, 0.8, "d3")
-    constraints = [d1, d2, d3]
-    for constraint in constraints:
-        g.add_constraint(constraint)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mfc="steelblue", mec="steelblue", fillstyle="right", markersize=10)
-    for p in points:
-        plt.text(p.x().value() + 0.02, p.y().value() + 0.02, p.name())
-    plt.gca().set_aspect("equal")
-
-    plt.show()
-
-
-def main4():
-    import matplotlib.pyplot as plt
-    # Initialize the graph
-    g = ConstraintGraph()
-
-    # Add the points
-    p1 = Point(0.0, 0.0, "p1")
-    p2 = Point(1.0, 0.0, "p2")
-    p3 = Point(-0.05, 0.05, "p3")
-    # p4 = Point(0.5, 0.03, "p4")
-    points = [p1, p2, p3]
-    for point in points:
-        g.add_point(point)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mec="indianred",
-             mfc="indianred", fillstyle="left", markersize=10)
-
-    # Add the constraints
-    d1 = DistanceConstraint(p1, p2, 1.0, "d1")
-    d2 = DistanceConstraint(p1, p3, 0.2, "d2")
-    pol = PointOnLineConstraint(p3, p1, p2, "pol1")
-    # d3 = DistanceConstraint(p1, p3, 0.8, "d3")
-    constraints = [d1, d2, pol]
-    for constraint in constraints:
-        g.add_constraint(constraint)
-
-    # d4.param.set_value(2.0)
-    # # g.compile_equation_for_entity_or_constraint(aparl3)
-    # x, info = g.initial_solve(d3)
-    # print(f"{info = }")
-    # g.update_points(aparl3, new_x=x)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mfc="steelblue",
-             mec="steelblue", fillstyle="right", markersize=10)
-    for p in points:
-        plt.text(p.x().value() + 0.02, p.y().value() + 0.02, p.name())
-    plt.gca().set_aspect("equal")
-
-    plt.show()
-
-
-def main5():
-    import matplotlib.pyplot as plt
-    g = ConstraintGraph()
-
-    # Add the points
-    p1 = Point(0.0, 0.0, "p1")
-    p2 = Point(0.4, 0.1, "p2")
-    p3 = Point(0.1, -0.1, "p3")
-    p4 = Point(0.5, -0.15, "p4")
-    points = [p1, p2, p3, p4]
-    for point in points:
-        g.add_point(point)
-
-    d1 = DistanceConstraint(p1, p2, 0.5, "d1")
-    d2 = DistanceConstraint(p3, p4, 0.55, "d2")
-    par = Parallel4Constraint(p1, p2, p3, p4, "par")
-    for constraint in [d1, d2, par]:
-        g.add_constraint(constraint)
-
-    plt.plot([p.x().value() for p in points], [p.y().value() for p in points], ls="none", marker="o", mfc="indianred")
-    plt.show()
-
-    g.remove_constraint(par)
-
-
-if __name__ == "__main__":
-    main2()

pymead/core/geometry_collection.py

@@ -21,7 +21,7 @@
 
 
 class GeometryCollection(DualRep):
-    def __init__(self):
+    def __init__(self, gui_obj=None):
         """
         The geometry collection is the primary class in pymead for housing all the available fundamental geometry
         types. Geometry, parameters, and constraints can be added using the nomenclature ``add_<object-name>()``.
@@ -39,6 +39,7 @@ def __init__(self):
             "dims": {},
         }
         self.gcs = ConstraintGraph()
+        self.gui_obj = gui_obj
         self.canvas = None
         self.tree = None
         self.selected_objects = {k: [] for k in self._container.keys()}
@@ -798,6 +799,10 @@ def add_constraint(self, constraint: GeoCon, assign_unique_name: bool = True, **
             self.gcs.add_constraint(constraint, **constraint_kwargs)
         except (OverConstrainedError, ValueError) as e:
             self.remove_pymead_obj(constraint)
+            self.clear_selected_objects()
+            if self.gui_obj is not None:
+                self.gui_obj.showColoredMessage("Constraint cluster is over-constrained. Removing constraint...",
+                                                4000, "#eb4034")
             raise e
         return constraint
 
@@ -862,8 +867,8 @@ def get_metadata():
         }
 
     @classmethod
-    def set_from_dict_rep(cls, d: dict, canvas=None, tree=None):
-        geo_col = cls()
+    def set_from_dict_rep(cls, d: dict, canvas=None, tree=None, gui_obj=None):
+        geo_col = cls(gui_obj=gui_obj)
         geo_col.canvas = canvas
         geo_col.tree = tree
         for name, desvar_dict in d["desvar"].items():

pymead/core/param.py

@@ -175,6 +175,9 @@ def set_lower(self, lower: float):
         if self._value is not None and self._value < self._lower:
             self._value = self._lower
 
+        if self.tree_item is not None:
+            self.tree_item.treeWidget().itemWidget(self.tree_item, 1).setMinimum(self.lower())
+
     def set_upper(self, upper: float):
         """
         Sets the upper bound for the design variable. If called from outside ``DesVar.__init__()``, adjust the design
@@ -189,6 +192,9 @@ def set_upper(self, upper: float):
         if self._value is not None and self._value > self._upper:
             self._value = self._upper
 
+        if self.tree_item is not None:
+            self.tree_item.treeWidget().itemWidget(self.tree_item, 1).setMaximum(self.upper())
+
     def get_dict_rep(self):
         return {"value": float(self.value()) if self.dtype == "float" else int(self.value()),
                 "lower": self.lower(), "upper": self.upper(),